1. Field of the Invention
The present invention relates to a device for detecting red eye, a program therefor, and a recording medium storing the program. More specifically, the present invention relates to a red-eye detection device installable in a digital camera or a laboratory system for digital photographs, a program for detecting red eye, and a computer-readable recording medium storing the program.
2. Description of the Related Art
The red-eye phenomenon (hereinafter simply referred to as red eye) caused by flash photography of people damages natural appearance of a photograph, which is not desirable. Therefore, various methods of automatically or semi-automatically detecting a red-eye area in a digital photograph image have been proposed for color correction or the like of the red-eye area after photography.
For example, a method of semi-automatic red-eye area detection is described in U.S. Pat. No. 5,990,973. In this method, an area including pixels of most reddish color is specified as a red-eye area corresponding to one eye in a frame that has been specified by a user as a rough frame including the red-eye area in a digital photograph image. A red-eye area corresponding to the other eye is then searched for according to a positional relationship or the like with the former red-eye area.
An automatic method has also been described (“Red Eye Detection with Machine Learning”, Sergey Ioffe, Proceedings of the Ninth IEEE International Conference on Computer Vision (ICVC 2003), Vol. 2, pp. 871-874, September 2003). In this method, reference data are prepared by using a machine learning method known as boosting, and a red-eye candidate area and a face area are detected in a digital photograph image by using the reference data. The red-eye candidate area in the face area is then confirmed as a red-eye area, and outline of the red-eye area is determined. Furthermore, various methods have been described in Japanese Unexamined Patent Publication No. 6(1994)-258732. For example, a red area and a skin-color area are detected in a digital photograph image according to a predetermined criterion set for pixel values in the Luv color specification system, and a red-eye area is detected by finding a logical product between the red area and a reversal of the skin-color area. Moreover, another method has been described in U.S. Pat. No. 6,278,491. In this method, a face area, an eye area in the face area, and an area of a red pupil in the eye area are serially detected in a digital photograph image according to a method based on neural network and principal component analysis.
However, red-eye areas in digital photograph images appear in various patterns, and learning or analyzing all the patterns in advance for setting a predetermined criterion is impossible in an automatic or semi-automatic red-eye detection method using the criterion. Therefore, failure of detection or erroneous detection of a red-eye area is inevitable. Furthermore, in a red-eye detection method using a predetermined criterion, failure of detection or erroneous detection always occurs for a red-eye area of a pattern of frequent appearance but not considered in learning in advance, or for an area of a pattern that has been considered as a red-eye area in learning in advance but is highly likely to be an area other than a red-eye area such as a red lamp.